Business Analyst, Machine Learning & AI Product (R1012235)

  • IQVIA
  • London, UK
  • 19/11/2018
Full time Data Science Data Engineering Machine Learning Data Analytics Artificial Intelligence Data Management Statistics Software Engineering

Job Description

We are looking for a confident, energetic and intellectually curious Product Business Analyst to join our London-based team. This is an exciting opportunity to be part of one of the world's leading Machine Learning Products in Healthcare teams, working to help our clients answer specific questions globally, make more informed decisions and deliver results.

The role

The Product Business Analyst will be responsible for eliciting, analyzing and managing the requirements needed for building Machine Learning applications for clients, in the capacity of a Product Manager role. The PBA will be responsible for arranging meeting with clients, understanding requirements, creating and maintaining the product backlog for each product.  The PBA will be required to support running the scrum processes, bridging between the client requirements and the product development team.  The will run the sprint planning meetings and work with both the developers and QA team to ensure the requirements are fully met and validated.  The PBA will provide demos to the stakeholders at the end of each sprint and work with the stakeholders to priority the next sprint’s work; will be coordinating and facilitating UAT testing to make sure the product meets user expectations; will be responsible for the day-to-day operations of the project and provide status updates to management when requested. The PBA will support with proposal and product materials preparation, blending innovation with pragmatism.      

Our ideal candidate

  • Knowledge of healthcare patient-level data, e.g. claims data, HER, hospital episodes, etc.or longitudinal data and studies
  • Passion and keen interest for developing cutting-edge Machine Learning products on healthcare data to server our clients
  • Background in epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilization, etc.
  • Knowledge of healthcare / life science issues involving Real-World Evidence.
  • Ability to perform day-to-day project management
  • Ability to gather requirements/business rules

Our ideal candidate: Tech Skills

  • Knowledge of UI development in plotly, javascript, CSS, Rshiny, tableau, qlikview
  • Knowledge of overall software development process
  • Knowledge of Team Foundation Server (TFS) or other backlog management system
  • Strong familiarity with Scrum/agile methodology

Bonus points for:

  • Background in bioinformatics.

The Team 

Our Machine Learning & Artificial Intelligence team within the Real-World & Analytics Solutions (RWAS) Technology division is a fast-growing group of collaborative, enthusiastic, and entrepreneurial individuals. In our never-ending quest for opportunities to harness the value of Real World Evidence (RWE), we are at the centre of IQVIA’s advances in areas such as machine learning and cutting-edge statistical approaches. Our efforts improve retrospective clinical studies, under-diagnosis of rare diseases, personalized treatment response profiles, disease progression predictions, and clinical decision-support tools.

You will join this high-profile team to work on ground-breaking problems in health outcomes across disease areas including Oncology, Neurology, Chronic diseases such as diabetes, and a variety of very rare conditions.

The Machine Learning & Artificial Intelligence Analytics team work hand-in-hand with statisticians, epidemiologists and disease area experts across the wider global RWE Solutions team, leveraging a vast variety of anonymous patient-level information from sources such as electronic health records. The data encompasses IQVIA’s access to over 530 million anonymised patients as well as bespoke, custom partnerships with healthcare providers and payers.

The Business Unit: Real-World & Analytics Solutions (RWAS) Technology

Real-World & Analytics Solutions (RWAS) is a market-leading, fast-growing and highly successful business, focusing upon delivering tangible business results to clients across healthcare value chain internationally, working with key decision-makers and business managers. RWAS teams help clients lever complex clinically rich patient-level healthcare datasets to understand healthcare treatment patterns and outcomes to make more informed decisions, and deliver results.

The RWAS Technology mission is to deliver world class and globally scalable technology platforms and analytics applied to complex and large scale clinical datasets, to support IQVIA’s ongoing and rapid growth in Real World Evidence, as well as the development of new product lines - this requires global leadership across technical and data architecture, software development and data visualization, privacy management, analytical methods, data science, machine learning, deep learning and natural language processing (NLP) - building upon 100s of novel technologies and methods either published in peer reviewed journals or patented by our team.

The solutions are delivered to a variety of clients across life-science, government, payor or provider organizations. The CoE also curates the largest collection de-identified Real-World Data in the world, from different patient care settings in 18 countries worldwide – the RWES Tech CoE is at the forefront of “Big Data” in healthcare.  Through its mission and skills, the RWES is transforming the way clients create new insights and deliver improved healthcare research and patient outcomes.

IQVIA is a strong advocate of diversity and inclusion in the workplace.  We believe that a work environment that embraces diversity will give us a competitive advantage in the global marketplace and enhance our success.  We believe that an inclusive and respectful workplace culture fosters a sense of belonging among our employees, builds a stronger team, and allows individual employees the opportunity to maximize their personal potential.